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DISCUSSION PAPER SERIES IZA DP No. 3635 Being Born Under Adverse Economic Conditions Leads to a Higher Cardiovascular Mortality Rate Later in Life: Evidence Based on Individuals Born at Different Stages of the Business Cycle Gerard J. van den Berg Gabriele Doblhammer-Reiter Kaare Christensen August 2008 Forschungsinstitut zur Zukunft der Arbeit Institute for the Study of Labor Being Born Under Adverse Economic Conditions Leads to a Higher Cardiovascular Mortality Rate Later in Life: Evidence Based on Individuals Born at Different Stages of the Business Cycle Gerard J. van den Berg VU University Amsterdam, IFAU Uppsala, Netspar, CEPR, IFS and IZA Gabriele Doblhammer-Reiter University of Rostock and Max Planck Institute for Demographic Research Kaare Christensen University of Southern Denmark, Danish Twin Registry and Danish Aging Research Center Discussion Paper No. 3635 August 2008 IZA P.O. 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A revised version may be available directly from the author. IZA Discussion Paper No. 3635 August 2008 ABSTRACT Being Born Under Adverse Economic Conditions Leads to a Higher Cardiovascular Mortality Rate Later in Life: Evidence Based on Individuals Born at Different Stages of the Business Cycle* We connect the recent medical and economic literatures on the long-run effects of early-life conditions, by analyzing the effects of economic conditions on the individual cardiovascular (CV) mortality rate later in life, using individual data records from the Danish Twin Registry covering births since the 1870s and including the cause of death. To capture exogenous variation of conditions early in life we use the state of the business cycle around birth. We find a significant negative effect of economic conditions early in life on the individual CV mortality rate at higher ages. There is no effect on the cancer-specific mortality rate. From variation within and between monozygotic and dizygotic twin pairs born under different conditions we conclude that the fate of an individual is more strongly determined by genetic and household-environmental factors if early-life conditions are poor. Individual-specific qualities come more to fruition if the starting position in life is better. JEL Classification: Keywords: I10, J14, C41, H75, E32, J10, N33, N13, I12, I18 longevity, genetic determinants, health, recession, life expectancy, cardiovascular disease, cancer, lifetimes, fetal programming, cause of death, developmental origins Corresponding author: Gerard J. van den Berg Department of Economics VU University Amsterdam De Boelelaan 1105 1081 HV Amsterdam The Netherlands E-mail: gjvdberg@xs4all.nl * We thank Angus Deaton, Hans Christian Johansen, Adriana Lleras-Muney, Bernard van Praag, Andreas Wienke, and participants at seminars at St. Gallen University, VU University Amsterdam, Groningen University, and INSEE-CREST, and conferences in Mölle/Lund and Berlin, for helpful comments. We also thank Axel Skytthe for help with the Danish twin registry data and Ingrid Henriksen, Mette Bjarnholt and Mette Erjnaes for help with the Danish historical time series data. 1 Introduction In many scientific disciplines, the interest in long-run effects of early-life conditions has been strongly increasing during the past years. In medical science, the “Developmental Origins” and “Fetal Programming” hypotheses, which state that certain diseases at high ages can be caused by deprivation in utero or around birth, has been confirmed by a range of studies, in particular for cardiovascular diseases (CVD) as outcome (see references below). More generally, the search for early origins as causes of CVD later in life has become an important focal point of research in medical science. In epidemiology and demography, various indicators of early-life conditions have been found to be associated with health and mortality later in life. At the same time, economists and sociologists are increasingly interested in the importance of parental income and socio-economic status as explanations for health later in life.1 In this paper we aim to combine the medical/epidemiological and economic contributions on long-run effects of early-life conditions, by analyzing the causal effect of economic conditions around birth on the individual rate of mortality due to cardiovascular diseases much later in life. For this purpose we use individual twin register data covering multiple birth cohorts, containing the dates of birth and death and the cause of death. In each of the above-mentioned disciplines, the empirical evidence often replies on indicators of early-life conditions for which it is questionable that they are exogenous causal determinants of health later in life. An association between such an indicator and health later in life then does not necessarily imply the presence of a causal effect of early-life conditions. Instead, the indicator and the health outcome may be jointly affected by related unobserved determinants. Consider for example parental income or wealth at birth. To some extent, this is determined by unobserved factors that also directly affect the morbidity and 1 Surveys and meta-studies of the epidemiological and medical evidence of associations of birth weight indicators and CVD later in life have been published in Poulter et al. (1999), Rasmussen (2001), and Huxley et al. (2007). The survey in Eriksson (2007) also focuses on medical early-life indicators measured after birth. Gluckman, Hanson and Pinal (2005) and Barker (2007) give overviews of the underlying medical mechanisms. Some studies also point at long-run effects on other diseases like type-2 diabetes and breast cancer. Pollitt, Rose and Kaufman (2005) provide a survey and meta-study of the “life course” literature on causal pathways in which early-life socio-economic status (SES) is associated with CV morbidity and mortality later in life. Galobardes, Lynch and Davey Smith (2004) survey studies on early-life SES and cause-specific mortality in adulthood. See also Case, Fertig and Paxson (2005) and Case, Lubotsky and Paxson (2002) and references therein, for influential studies focusing on economic household conditions early in life. 2 mortality of individuals at higher ages. An association between parental income at birth and longevity may then be due to the fact these have shared determinants. Similar problems arise with the use of birth weight or weight at gestational age, as has been acknowledged in the medical and epidemiological literature. These measures depend on genetic determinants, and it is not clear to what extent these can be controlled for by conditioning on additional covariates (see arguments made in e.g. the surveys of Poulter et al., 1999, Rasmussen, 2001, Huxley et al., 2007, Lawlor, 2008, and also Ben-Schlomo, 2001, and Järvelin et al., 2004). We deal with this methodological problem by using the state of the business cycle at early ages as indicators of early-life conditions. Transitory macroeconomic conditions during pregnancy of the mother and early childhood are unanticipated and exogenous from the individual point of view, and they affect income for many households. In a recession, the provision of sufficient nutrients and good living conditions for infants and pregnant women may be hampered, and the stress level in the household may be higher than otherwise. It can be argued that the only way in which the indicators can plausibly affect high-age mortality is by way of the individual early-life conditions (in Section 2 we address this in more detail). This means that such indicators do not give rise to endogeneity and simultaneity biases. The approach to use transitory features of the macro environment as indicators of individual early-life conditions, rather than unique characteristics of the newborn individual or his family or household, has recently become popular. Doblhammer (2004) uses month of birth, whereas other studies compare individuals born during extreme events like epidemics, wars, and famines, to those born outside of the periods covered by these events (see e.g. Almond, 2002). Bengtsson and Lindström (2000, 2003) use the transitory component of the local price of rye around birth and the local infant mortality rate. Van den Berg, Lindeboom and Portrait (2006) use the state of the business cycle at early ages as determinants of all-cause individual mortality using Dutch data on births in 1815-1902. Cutler, Miller and Norton (2007) use the Great Depression in the Dust Bowl area in the US.2 One may argue that results based on extreme events are hard to extrapolate because long-run effects may be non-linear in the hardships early in life. This makes business cycles and 2 They do not find evidence of a long-run effect on CVD among those who survive until 1992, from interviews that were held every 2 years since 1992. One explanation put forward by the authors is that deaths due to CVD between interview dates may be underreported. This suggests that registered death causes may be more informative on long-run CV effects than self-reported health statuses. Another explanation put forward is that there may have been sufficient opportunities for consumption smoothing, and sufficient relief payments, to mitigate adverse effects of this recession. 3 seasons potentially more useful as indicators of early-life conditions than severe epidemics or famines. Moreover, the latter type of events may lead to high infant mortality and dynamic selection of the fittest in the cohort, which complicates the statistical analysis.3 The Danish Twin Registry data we use in the present paper are uniquely equipped for our purposes, because (i) they contain the exact dates of birth and death, (ii) they cover birth cohorts over a rather large time frame, covering many transitory fluctuations in the economy, (iii) in each birth cohort that we consider, a sufficiently large fraction of individuals has been observed to die, and (iv) they contain the cause of death. Other data sets like those in the Human Mortality Database only contain death cause information for recent birth cohorts in which most individuals are still alive (see e.g. Andreev, 2002, for Danish data). Alternatively, birth dates in data sets are time-aggregated into intervals covering more than a year, which is fatal for our approach, or they only contain a small number of birth cohorts around some extreme event, and/or they contain health outcomes but not mortality outcomes. A fifth and major additional advantage of the twin data is that the observation of zygosity of the twin pair allows us to assess the relative importance of genetic factors, shared environmental factors, and individual-specific factors, as determinants of CV mortality and longevity. More specifically, it allows us to assess to what extent the relative importance of family/household-specific and individual-specific determinants depends on the business cycle at birth, and thus on economic conditions early in life. From this we can infer whether the fate of an individual born under adverse conditions is more strongly shaped by the family background vis-à-vis the individual’s own characteristics than if (s)he were born under better conditions.4 As above, we address the presence of such interactions by using exogenous indicators of economic conditions early in life, which is a methodological advantage over the use of family income or social status as an interacting variable for genetic determinants. One may argue that a twin birth poses a heavier burden on the household than the birth of a single child. This merely means that the exogenous variation in early-life conditions will be expressed more strongly through twins, but it 3 For clarity, note that we are not concerned with instantaneous “period” effects of recessions on health. Ruhm (2000) shows that recessions may have protective instantaneous health effects in modern economies. 4 Black, Devereux and Salvanes (2007) exploit differences in twins’ within-pair birth weight to detect long-run effects of birth weight on economic outcomes. Our data do not provide observations of birth weight, and more in general we do not observe within-pair differences in early-life conditions. 4 obviously does not affect the existence or non-existence of the causal effect from these conditions. In this sense, a twinbirth in a mild recession should have the same effect as a single birth in a sufficiently severe recession. Another issue is whether the composition of the (twin) birth cohorts systematically varies over the business cycle. We investigate this by examining fluctuations in birth rates and twinning rates, and by using additional survey data on the composition. Long-run effects of economic conditions early in life may work through nutrition, disease exposure, household stress levels, and the level of living comfort in the household. We shed some light on these by studying the importance of the timing of the macro fluctuations around the year of birth and by interacting the effects with regional indicators and the degree of urbanization. The Danish twin data have been used by many other studies. These often exploit or study the similarities between MZ and DZ twins (see Skytthe et al., 2002, and Harvald et al., 2004, for overviews). Christensen et al. (1995, 2001) compare patterns of mortality across age and cohort intervals in the twin data to the corresponding intervals in the general population, and they conclude that among adults the patterns are usually the same. Wienke et al. (2001) replicate this for coronary heart disease, and they reach the same conclusion. This suggests that twins are not necessarily different from single births, when it comes to the mortality distribution at higher ages, which supports the relevance of our analyses. Knowledge on the magnitude of long-run effects may have important policy implications. If being born under certain adverse conditions increases the individual CV mortality rate in the long run (and therefore has a negative effect on longevity) then the value of life is reduced for those affected, and this would increase the benefits of supportive policies for such groups of individuals. The long-run effect of early-life conditions on the mortality rate may be smaller than the instantaneous effect of current conditions, but the former exert their influence over a longer time span. Moreover, the presence of a time interval between infancy and the manifestation of the effect implies that there is a scope for identification and treatment of the individuals at risk. Specifically, young individuals born under adverse conditions can be targeted for a screening of CVD markers and predictors, and those who have unfavorable test values are amenable to preventive intervention. Note that screening and preventive intervention policies can also be justified by proven associations between risk factors like birth weight and parental income on the one hand, and CV mortality on the other. The analysis in this paper also allows for a more modest motivation, namely the study of whether individuals born in a recession have a higher CV mortality 5 rate later in life. If one is concerned about health inequality due to variation in the state of the business cycle at birth, then evidence of such a long-run effect provides a rationale for macroeconomic stabilization policy. Moreover, it may then be sensible to target policy at infants born in recessions. Their mortality later in life could be significantly reduced if their conditions are improved upon, for example by monitoring their health shortly after birth and by providing food, housing, and health care. It should be emphasized that living conditions in Denmark around 1900 were relatively good in comparison to most other countries at the time and in comparison to many developing countries today. Life expectancy was the highest in the world (Johansen, 2002a). Health insurance coverage was high. Denmark arguably had the best health care system in the world in terms of well-being of mothers and infants (see Løkke, 2007, for a detailed survey). Insurance societies paid out sickness absence benefits to employed workers who had fallen ill. In general, there was an extensive poor relief system. Nevertheless, one may conjecture that nutritional conditions in Denmark around 100 years ago were different from current conditions. In this respect it is important to point out that recent medical research has shown that not just fetal malnourishment is associated with long-run effects on CVD outcomes, but, more in general, that discrepancies between early-life conditions in utero and shortly after birth on the one hand, and later lifestyle on the other hand, lead to long-run effects on CVD outcomes (see e.g. Mogren et al., 2001, and Holemans, Caluwaerts and André Van Assche, 2002; see also Fogel, 1997, for an overview). In this sense, our study is also of importance for modern societies. Individuals born in low-income household who have very high nutritional intakes later in life may be particularly at risk for adverse CVD outcomes at higher ages.5 For current developing countries, which in certain aspects could be regarded as similar to or worse off than Denmark in the period evaluated in the present paper, the existing literature has focused on inequalities in infant and child mortality by household socioeconomic status, since there are typically no long run data registers (see Sastry, 2004). In this sense, our paper aims to complement these studies by studying long run mortality effects. The paper is organized as follows. Section 2 presents the data and discusses variables that we use in the analyses. Section 3 displays readily observable data 5 Note that the virtual disappearance of infant mortality implies that those who would have died if born under adverse conditions in the nineteenth century nowadays survive into adulthood. This can be seen as a factor that contributes to the potential relevance of long-run effects in modern societies. 6 features that confirm the existence of the causal mechanisms that we are interested in. Section 4 describes the formal empirical analyses and the results. In this section we also examine whether the composition of mortality determinants among newborns and newborn twins varies over the cycle in a systematic way. Section 5 concludes. 2 2.1 The data Individual records from the Twin Registry Our individual data records are derived from the Danish Twin Registry. This registry has been created over decades in an attempt to obtain a comprehensive sample of all same-sex twins born since 1870 and surviving as twins until at least age 6 (and it also includes many different-sex twins). We refer to studies listed in Section 1 for detailed descriptions of the registry and the way it has been collected. A number of factors determine the selection that we use for the empirical analysis. Most importantly, we restrict ourselves to twins for whom sufficient information is available on the most important variables. A crucial aspect is that most individuals born in the chosen birth interval should be observed to die. In recent cohorts, almost all individuals are still alive, so that these would merely add right-censored drawings from the lifetime duration distribution. At the same time, it is not clear whether the underlying longevity determinants exert a similar effect as in earlier cohorts, because the increasing welfare in later years may have led to a dampening of the effect of a recession and other economic hardships on a household’s food provision. This implies that we should consider earlier cohorts. In the late 19th century, Denmark had about 2.3 million inhabitants, of whom about 0.35 million lived in Copenhagen. The economy had a large agricultural sector, accounting for almost half of GDP and the workforce, but this sector itself had to some extent already been industrialized. The economy was open, and export volume and the business cycle were sensitive to events in Britain. The country faced substantial GDP growth after 1870 (see e.g. Statistics Denmark, 1902, Christensen, 1985, Johansen, 1985, Henriksen and O’Rourke, 2005, and Greasley and Madsen, 2006, for details of the Danish economy in the late 19th century). For our purposes, it is important to point out that in 1907 unemployment benefits were introduced in Denmark, with the explicit objective to dampen adverse effects of the business cycle on the economic well-being of the Danish population. To keep the heterogeneity in early-life societal conditions within bounds, we therefore restrict attention to those born before 1907. Among 7 the cohorts born before 1910, the fraction of twins per birth year with known zygosity increases with the birth year, so adding some cohorts born shortly after 1907 to samples with known zygosities would result in samples in which the later-born cohorts dominate. In any case, it turns out that our results are not sensitive with respect to small changes in the cut-off year. We restrict attention to same-sex twin pairs with known zygosity, for which both twins survive until at least January 1, 1943. This is because for this group the highest efforts have been made to collect the death cause and date. In the registry, the death cause is unobserved for all deaths before 1943, and the death cause and date are unobserved for most deaths of different-sex twin pairs or twin pairs with unknown zygosity after 1943. The restriction to survival until 1943 is not a serious limitation in the sense that we are particularly interested in mortality at higher ages. Finally, we delete births in 1870–1872 because the macro-economic indicator (see below) seems to be unreliable for those years. The latter reduces the sample size by only 2%. As a result, we use a sample of all 6050 same-sex twin members with known zygosity, born in 1873–1906, for which both twins survive until at least January 1, 1943. The birth and death dates and the resulting individual lifetime durations are observed in days. The observation window ends on January 6, 2004, so individuals still alive then (0.4%) have right-censored durations. Table 1 gives some sample statistics. We should emphasize that the death date is observed for more than 95% of the individuals in our sample, and for 99% of the latter we also observe the death cause. The death cause is classified according to the ICD system, versions 5–8, at the 3-digit level. These are grouped into 12 categories, which are subsequently grouped into our 3 main death causes: “cardiovascular” (death due to cardiovascular malfunctions or diseases, including apoplexy),6 “cancer” (death due to malignant neoplasms or congenital malformations - the latter concerns less than 0.1% of our sample) and “other” (including death due to tuberculosis, other infectious diseases, diseases of the respiratory, digestive or uro-genital system, suicide, or accidents). The first of these three death causes is the most prominent in our sample. Its frequency decreases as a function of the birth year. Among those born in the 1870s, 60% are observed to die from CVD, whereas among those born in the 1900s, this is 50%. Note that the former group contains more elderly individuals due to the requirement of survival until 1943.7 6 In the “cardiovascular” category, the most common 3-digit death causes are cerebral haemorrhage, acute myocardial infarction, chronic ischemic heart disease, arteriosclerotic heart disease including coronary disease, and acute but ill-defined cerebrovascular disease. 7 See National Board of Health, 1983, Johansen, 1985, and Andreev, 2002, for detailed 8